Lifecycle Role Decomposition
Lifecycle Role Decomposition translates human work roles into lifecycle responsibility boundaries that agent systems can execute, confirm, trace, roll back, and accept.
Lifecycle Role Decomposition is the translation step between human work models and real multi-agent systems. It does not merely rename PM, Architect, Developer, Reviewer, or QA as agents. It decomposes the responsibility behind those roles into lifecycle objects such as Context, Role, Plan, Confirm, Trace, and Delivery so an agent system can execute, confirm, trace, audit, roll back, and accept work.
The problem it names
The problem it names is that human roles carry implicit authority and responsibility, while agents do not automatically inherit those boundaries. A Reviewer Agent may produce comments, but unless its review boundary, confirmation authority, evidence obligation, and delivery-transition control are explicit, the system still only has a role label. The label looks familiar to the operator, but the accountability structure never entered the system.
Why existing approaches are not enough
Manual workflow graphs can show which agent runs next, and orchestration frameworks can execute those graphs. They usually do not infer which responsibilities must be separated, which decisions require confirmation, which traces must survive, or which states become accepted and inheritable. Lifecycle Role Decomposition names the missing translation layer before execution begins.
How it relates to AI Agent Lifecycle
Within AI Agent Lifecycle, Lifecycle Role Decomposition sits at the boundary between human-readable work practice and protocol-governed agent work. It keeps role, plan, confirmation, trace, rollback, and delivery from remaining implicit. It is a supporting decomposition pattern, not an added first-stage public concept.
White paper source trace
Lifecycle Role Decomposition is adjacent to GAIC through human-role responsibility mapping; R3K-0 did not assign a direct chapter/table/MRO anchor for this route.
The page explains the role-decomposition practice that supports GAIC-style human-role and MAS responsibility objects.
A role decomposition separates who owns intent, who can authorize action, who reviews evidence, and who accepts or remediates the outcome.
This source trace is author-analytical. It is not legal advice, certification, legal compliance proof, regulator approval, vendor ranking, procurement guidance, or a claim that MPLP is required.
Evidence route
The evidence route starts with the second Define The AI Agent Lifecycle essay, where human software work is decomposed into lifecycle objects and responsibility boundaries. MPLP is the protocol path for the vocabulary; SoloCrew is the delivery proof path where human-facing roles need to become usable without losing accountability.